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Why visualize?

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Interest in data visualization as a fraction of the maximum interest recorderd (using Google Trends). The blue line represents a moving average.

Interest in data visualization as a fraction of the maximum interest recorderd (using Google Trends). The blue line represents a moving average.

Visualization as communication

  • main goal is to communicate patterns in data
  • we are wired to learn from seeing

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Charles Minard's visualization of Napoleon's Russian campaign of 1812.

Charles Minard’s visualization of Napoleon’s Russian campaign of 1812.

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An example

GDP per capita and life expectancy across time

First attempt

Transforming the axis

Grouping time, adding population

Animated plots (using gganimate)

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Knowledge and understanding

  • demonstrate knowledge of the theoretical and practical construction of visualisations, and
  • demonstrate understanding of how the type of data impacts the visualisation and what components are appropriate.

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Competence and skills

  • demonstrate the skill to independently, using software, visualise various types of data,
  • demonstrate the ability to make appropriate choices in designing visualisations, and
  • demonstrate the ability to in writing present and discuss visualisations in dialogue with others.

Judgement and approach

  • demonstrate the ability to assess visualisations with respect to clarity, accessibility and ethics, and
  • demonstrate insight into the importance of the design of visualisations with respect to communicative properties, accessibility and ethics.

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Course structure

Topics

  • introduction to R and R Studio
  • introduction to ggplot2
  • basics of data visualizations
  • visualizations with one variable
  • visualizations with several variables
  • maps
  • interactive and animated visualizations

Learning activities

  • lectures
  • text
  • worked examples

Examination

Assessment

  • quizzes
  • assignments
  • project

.pull-left[ ### Peer feedback

the assignment and project will be reviewed through peer-feedback ]

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.pull-left[ ## Course literature

  • Data visualization: Charts, Maps, and Interactive Graphics (Grant, 2018). Available through LUBsearch.
  • A Layered Grammar of Graphics (Wickham, 2010). Available online for free. ]

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Other resources

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Good luck!

References

Chang, W. (2013). R Graphics Cookbook: Practical Recipes for Visualizing Data. 1 edition. Beijing Cambridge Farnham Köln Sebastopol Tokyo: O’Reilly Media. 416 pp. ISBN: 978-1-4493-1695-2.

Grant, R. (2018). Data Visualization: Charts, Maps, and Interactive Graphics. 1 edition. Boca Raton: Chapman and Hall/CRC. 248 pp. ISBN: 978-1-138-70760-3.

Reinsel, D., J. Gantz, and J. Rydning (2018). The Digitization of the World: From Edge to Core. US44413318. MA, USA: IDC, p. 28.

Wickham, H. (2010). “A Layered Grammar of Graphics”. In: Journal of computational and graphical statistics 19.1, pp. 3-28. ISSN: 1061-8600. DOI: 10.1198/jcgs.2009.07098. URL: http://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07098 (visited on mar. 13, 2020).